eBike measurements for fatigue monitoring and maneuver identification tasks
datacite.FundingReference.funderName | Europäische Union | |
Contributing person | Kästner, Markus | |
Additional geographical or spatial references | Dresden | |
Description of the data | The dataset mainly includes measurement time series files. Additionally, pictures are included to document the experimental setup and a python script is provided in order to facilitate the data access. | |
Type of the data | Software | |
Type of the data | Dataset | |
Type of the data | Image | |
Total size of the dataset | 1181417795 | |
Author | Heindel, Leonhard | |
Author | Hantschke, Peter | |
Author | Kästner, Markus | |
Upload date | 2022-09-26T10:44:39Z | |
Publication date | 2022-09-26T10:44:39Z | |
Publication date | 2026-06-10T15:44:27Z | |
Data of data creation | 2022 | |
Publication date | 2022-09-26 | |
Abstract of the dataset | This dataset provides acceleration and strain measurements from a sensor equipped eBike, which were collected for the development of new methods for fatigue damage monitoring and maneuver identification tasks. | |
Public reference to this page | https://opara.zih.tu-dresden.de/handle/123456789/2617 | |
Public reference to this page | https://doi.org/10.25532/OPARA-189 | |
dc.language | eng | |
Publisher | Technische Universität Dresden | |
Licence | Attribution 4.0 International | |
URI of the licence text | http://creativecommons.org/licenses/by/4.0/ | |
Specification of the discipline(s) | 4 | |
Title of the dataset | eBike measurements for fatigue monitoring and maneuver identification tasks | |
Software | Python | |
Project abstract | The objectives of the project are the development of fundamental digital methods for monitoring and increasing the reliability of highly integrated mechatronic systems that can be transferred to other engineering problems. The methods are to be developed within the framework of the project using the electric bicycle as an example, always with a view to the transferability and utilization of the research results to other vehicles with electric drives. These methods are a prerequisite for new business models of system providers that link product, application and service. | |
Project title | ePredict |
Files
Original bundle
- Name:
- Heindel2022_dataset.zip
- Size:
- 1.1 GB
- Format:
- Description:
- zip archive of measurement data
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